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Enjoy today’s breakdown of news, research, events & jobs within quantum.

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IN TODAY’S ISSUE:

Tags: SUPERCONDUCTING SOFTWARE HARDWARE ERROR CORRECTION CHEMISTRY APPLICATION ALGORITHMS QUANTUM METROLOGY QUANTUM ANNEALING

• IBM reveals its quantum computing roadmap, detailing plans up to 2033

• Recent research highlights the use of "gap engineering" to mitigate quasiparticle poisoning in superconducting circuits,

• A review explores the potential of metalloporphyrins as building blocks for quantum information science

• The QuADS algorithm combines quantum and classical techniques for continuous optimization, outperforming traditional methods

• Researchers explore using network states for quantum metrology to improve precision and privacy in distributed quantum sensing

• A study compares quantum and classical algorithms for energy coalition formation, finding that quantum solvers like D-Wave can achieve competitive performance and runtime scaling in optimizing power flows for decentralized energy management

• Plus, a study using QML for energy efficient wireless communications, a new quantum linear response formulation for simulating photoinduced processes, and Ripple University Blockchain Research Initiative explores the intersection of blockchain and quantum computing.

Check out NEW POLLS!

BRIEF BYTES

NEWS FOR THOSE IN A HURRY

• Linear response theory is essential in quantum chemistry for understanding photoinduced processes but is difficult to simulate for large systems with strong electron correlation. A new quantum linear response formulation using quantum computers to facilitate these simulations has been introduced. This study presents a resource-efficient qLR theory suitable for near-term quantum computers and identifies two promising approaches for simulating excited state potential energy curves and absorption spectra.

• A study proposes QML to improve the energy efficiency of reconfigurable intelligent surface assisted communication with rate-splitting multiple access. By using QML, the system can optimize transmission precoding and RIS phase shifting more efficiently which would achieve comparable performance to conventional methods but with reduced complexity. This approach would improve the energy efficiency of next-generation wireless communications.

• Ripple’s University Blockchain Research Initiative is collaborating with Professor Massimiliano Sala from the University of Trento to explore the intersection of blockchain and quantum computing. Professor Sala highlights the vulnerabilities quantum computing poses to blockchain security and emphasizes the need to transition to quantum-resistant cryptographic systems. He discusses the challenges and advancements in developing these systems, the role of algebra and coding theory, and the importance of global collaboration and updated education to prepare for quantum threats.

• Emitter dephasing, primarily caused by acoustic phonons, is a major issue in the performance of solid-state single-photon sources. This study shows that by selectively coupling a WSe2 monolayer quantum dot to a spectral cavity resonance, it is possible to engineer and improve the coherence of emitted photons.

• This study experimentally investigates a three-qubit controlled-CPHASE-SWAP gate on superconducting circuits and achieves a high fidelity with a duration comparable to single-qubit and two-qubit gates. Instead of decomposing quantum algorithms into single-qubit and two-qubit gates, solutions using multi-qubit gates can reduce computational resources.

• Also, IBM SVP Darío Gil provides a walk-through and exceptional explanation of quantum computer:

TOP HEADLINES IN NEWS & RESEARCH

NEWS

Tags: SUPERCONDUCTING SOFTWARE HARDWARE

IBM REVEALS QUANTUM ROADMAP UP TO 2033

BRIEF BYTE:  Jerry Chow, IBM Fellow and Director of Quantum Systems & Runtime Technology, reviews IBM Quantum roadmap over the next 9 years. Quick 5-minute video worth watching.

NEWS

Tags: SUPERCONDUCTING ERROR CORRECTION

“GAP ENGINEERING” FOR REDUCING DECOHERENCE

BRIEF BYTE:  Superconducting circuits suffer from quasiparticle poisoning which causes decoherence. Recent research reveals that engineering the energy landscape of these circuits can mitigate this issue by ensuring quasiparticles quickly thermalize with their environment.

WHAT HAPPENED: 

• Superconducting circuits experience unwanted electronic excitations, known as Bogoliubov quasiparticles, which disrupt quantum information processing by causing decoherence.

• The team conducted experiments on transmon qubits, observing that quasiparticles quickly thermalize with the cryostat temperature. They also noted that the quasiparticle tunneling rate increases with temperature, suggesting that the energy distribution of quasiparticles is influenced by the thermal environment.

• The study suggests that "gap engineering," or modifying the spatial profile of the superconducting gap energy, can keep quasiparticles away from sensitive areas and reduce their impact.

WHY IS THIS IMPORTANT:

• Understanding and controlling quasiparticle behavior using gap engineering can reduce the effect of quasiparticle poisoning which may lead to advances in maintaining coherence in superconducting qubits, as well as improve the overall performance and stability of superconducting circuits.

RESEARCH

Tags: CHEMISTRY APPLICATION 

OVERVIEW OF METALLOPORPHYRINS AS BUILDING BLOCKS FOR QUANTUM INFORMATION SCIENCE

BRIEF BYTE: This paper reviews the use of metalloporphyrins, a class of molecules with unique optical and electrical properties, as building blocks for quantum information science. It highlights recent advances in porphyrin-based molecular qubits and explores their potential for creating quantum logic gates.

WHY: 

• Metalloporphyrins are of particular interest due to their ability to accommodate metal atoms and ions, which can be used to create stable and scalable qubits. They can exhibit significant coherence times and can be easily controlled using microwave or radio-frequency pulses. By linking multiple porphyrins, the study presents the possibility of constructing quantum logic gates.

• This review differentiates itself by focusing on the interdisciplinary approach of combining chemistry and physics to develop practical quantum technologies. Unlike traditional solid-state systems, the chemical synthesis of porphyrins would offer the unique opportunity to construct quantum information systems from the atomic level up.

HOW: 

• The researchers synthesized metalloporphyrins with various metal ions to form stable molecular qubits and investigated their electronic and magnetic properties.

• They thoroughly characterized the optical and electronic properties of these metalloporphyrins using techniques such as electron paramagnetic resonance and nuclear magnetic resonance to study the spin dynamics and coherence properties of the qubits.

• The formation of quantum logic gates is explored by linking multiple porphyrin units and analyzing their magnetic interactions.

RESULTS: 

• Porphyrin-based molecular qubits exhibited coherence times on the order of microseconds, which is comparable to other leading qubit technologies. This extended coherence time indicates their suitability for quantum information processing applications.

• The ability to control and manipulate spin states in porphyrins was confirmed through precise microwave pulse sequences which allowed for the successful implementation of quantum gates.

• The creation of extended porphyrin frameworks demonstrated the potential for building scalable quantum systems. These frameworks maintained coherence and facilitated interactions between qubits.

RESEARCH

Tags: ALGORITHMS

OVERVIEW OF CONTINUOUS OPTIMIZATION BY QUANTUM ADAPTIVE DISTRIBUTION SEARCH

BRIEF BYTE: The quantum adaptive distribution search algorithm is introduced; a combination of Grover adaptive search and the classical covariance matrix adaptation evolution strategy that efficiently handles continuous optimization.

WHY: 

• Continuous optimization, especially for nonconvex functions, is relevant across various fields. Traditional optimization methods often struggle with local optima and high computational costs. The integration of quantum computing techniques promises speedups, but while Grover adaptive search provides a quadratic improvement in performance, its uniform search approach is not optimal for practical applications.

• By combining Grover adaptive search with classical covariance matrix adaptation evolution strategy, the quantum adaptive distribution search algorithm offers a more refined search process that adapts to the optimization landscape. This approach is efficient and may potentially reduce the computational resources required and improve the likelihood of finding global optima.

HOW: 

• The study applies QuADS to a variety of test functions with different characteristics to evaluate its performance. These functions include common benchmarks in optimization literature, such as the Rastrigin, Ackley, and Griewank functions. The performance of QuADS is compared against both GAS and CMA-ES to highlight its advantages.

• The algorithm starts with an initial mean and covariance matrix, defining a multivariate normal distribution.

• Using amplitude amplification, the algorithm samples points from the defined distribution and evaluates their function values.

• The distribution parameters are updated based on the sampled points, incorporating information about the optimization landscape to refine the search process.

• The threshold for the quantum search is updated using a moving average of the best function values obtained, ensuring that the search focuses on promising regions.

RESULTS: 

• QuADS consistently outperformed both GAS and CMA-ES in terms of the number of oracle calls required to find the global optimum across the test functions.

• The adaptive distribution update strategy allowed QuADS to navigate the optimization landscape more effectively and reduce the likelihood of getting trapped in local optima.

• QuADS had a smaller increase in computational cost with increasing dimensionality compared to other methods which highlights its potential for high-dimensional optimization problems.

RESEARCH

Tags: QUANTUM METROLOGY

OVERVIEW OF QUANTUM-ENHANCED METROLOGY WITH NETWORK STATES

BRIEF BYTE: Researchers explore the potential of using quantum correlations within network states for quantum metrology. The authors derive a general bound on the precision achievable when using network states for estimating global parameters and introduce a probabilistic protocol that can achieve the Heisenberg limit in quantum metrology.

WHY: 

• Quantum metrology uses quantum properties to achieve higher precision measurements than classical methods. Traditionally, entangled states like Greenberger-Horne-Zeilinger states have been used to achieve high precision. However, distributing and maintaining such entangled states over a network is challenging due to decoherence.

• This paper addresses these challenges by focusing on more practical network states and showing how they can be used effectively for quantum metrology, even if they don't initially appear to be as powerful as GHZ states.

• The authors derive a general upper bound on the precision of estimating a global parameter using network states. This bound highlights the necessity of genuine multipartite entanglement for achieving quantum advantages. The bound can also act as an entanglement witness to identify genuine multipartite entanglement within the network.

HOW: 

• The network state is represented using a hypergraph where vertices represent sensors (local sites) and hyperedges represent entanglement sources. Each local site applies operations based on the received entangled state.

• The authors derive a lower bound on the mean squared error for estimating a global parameter, considering both the sensing task and the network's architecture.

• A detailed probabilistic protocol is developed where local postselection is used to achieve the Heisenberg limit. This involves preparing GHZ states, acquiring local signals, and performing measurements that maintain the privacy of local parameters.

RESULTS: 

• The derived bound shows that the mean squared error for any deterministic protocol is limited by the standard quantum limit unless genuine multipartite entanglement is present in the network.

• The introduced probabilistic protocol can achieve the Heisenberg limit when successful which is an improvement in precision over deterministic protocols.

• The probabilistic protocol ensures that local parameters remain private which is a key concern in distributed quantum sensing.

• The study demonstrates that the architecture of the network significantly influences the achievable precision which highlights the importance of network design in quantum metrology.

PREPRINT

Tags: ALGORITHMS QUANTUM ANNEALING

OVERVIEW OF A COMPETITIVE SHOWCASE OF QUANTUM VERSUS CLASSICAL ALGORITHMS IN ENERGY COALITION FORMATION

BRIEF BYTE: This paper compares the performance of quantum and classical algorithms in the context of energy coalition formation for the purpose of decentralized and sustainable energy management.

WHY: 

• Energy coalition formation involves complex optimization problems that classical solvers struggle to handle efficiently as the number of agents increases. This study explores the potential of quantum computing to solve these problems more effectively.

• Unlike previous studies, this work not only benchmarks various algorithms but also proposes the transformation of the coalition structure generation problem into an induced subgraph game to make it more compatible with quantum algorithms.

• The study applies the proposed methodologies to a real-world problem of forming energy coalitions among consumers in a distribution network. This involves optimizing power flows to minimize network management costs while considering constraints such as power demand, supply, and distribution losses.

HOW: 

• The energy coalition formation problem is formulated as a CSG problem, where the goal is to partition consumers into coalitions to maximize the collective benefits while minimizing the network management costs.

• The CSG problem is transformed into an ISG, where the coalition values are represented as pairwise interactions in a weighted graph. This is for more efficient optimization using quantum algorithms.

• The study implements various classical and quantum algorithms,. Classical solvers include exact classical solver, Tabu search, simulated annealing, and QB-solve. Quantum solvers include quantum annealing on D-Wave hardware and QAOA on both simulators and IBM hardware.

• The performance of these algorithms is benchmarked based on solution quality and runtime using real-world data and randomly generated problem instances.

RESULTS: 

• D-Wave and QB-solve demonstrate comparable solution quality with D-Wave showing competitive performance against classical solvers. QAOA on simulators shows slightly lower but close solution quality to D-Wave, while QAOA on hardware performs worse.

• D-Wave and QB-solve exhibit favorable runtime scaling compared to classical solvers, especially as the number of consumers increases. QAOA on simulators scales polynomially but sub-optimally, and on hardware, it shows a larger prefactor in runtime scaling.

• Overall, the transformation of CFG to ISG reduces computational complexity to make the problem more tractable for quantum algorithms.

EVENTS

• Thursday, May 23 | QED-C Office Hours — Learn more about a career in QIST w/ Christopher Bishop

• Tuesday, May 28 | Results w/ QuEra “Resilient Networks: Quantum Solutions Using Neutral Atoms for Optical Fiber Optimization in Telecommunication

• Now - May 31 | Register for Google/X-Prize Quantum Challenge

JOBS POSTED WITHIN LAST 24 HOURS

• Penn State University Postdoctoral Scholar - Photoemission Spectroscopy on Quantum Materials | University Park, PA

• Brookhaven National Laboratory Scientific Associate Quantum Imaging | Upton, New York $69K - $87.6K

UNTIL TOMORROW.

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